How does risk interplay with trust in pre-and post-purchase intention to engage: PLS-SEM and ML classification approach

IF 4 Q2 BUSINESS Journal of Marketing Analytics Pub Date : 2024-09-04 DOI:10.1057/s41270-024-00341-y
Nora Sharkasi, Gomaa Agag
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Abstract

This study explores the effect of perceived risk PR and perceived affective and cognitive trust, PAT and PCT, respectively, on the intention to engage with Facebook FB adverts. Most of the literature explores the intention to engage pre-purchase, and only limited studies address all behavioral manifestations of the intention to engage -other than eWoM- post-purchase. In this study we explore the effect of PR, PAT and PCT on the intention to endorse, comment, and pass-on in the pre- and post-purchase when satisfied or dissatisfied. We collected quantitative data from young FB users in Southeast Asia, aged between 17 and 30. By supplementing the PLS-SEM analysis with accuracy scores resulting from classification-based machine learning (ML) algorithms, we explore the mediating effect of PR in the pre-purchase stage and its moderating effect in the post-purchase intention to engage. Our findings support the negative mediation effect of PR on the association between PAT and PCT and the intention to comment, and its positive mediation to endorse and share pre-purchase. Whereas the PR positive moderation effect is confirmed in the post-purchase intention to engage. The study proposes several academic and managerial implications.

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在购买前和购买后的参与意愿中,风险与信任是如何相互作用的:PLS-SEM 和 ML 分类方法
本研究探讨了感知风险 PR 和感知情感与认知信任(分别为 PAT 和 PCT)对 Facebook FB 广告参与意愿的影响。大多数文献探讨的是购买前的参与意愿,只有有限的研究探讨了购买后参与意愿的所有行为表现(除电子世界之外)。在本研究中,我们探讨了 PR、PAT 和 PCT 对购买前和购买后满意或不满意时的支持、评论和传递意向的影响。我们收集了东南亚 17 至 30 岁年轻 FB 用户的定量数据。通过使用基于分类的机器学习(ML)算法得出的准确度分数对 PLS-SEM 分析进行补充,我们探索了公关在购买前阶段的中介效应及其在购买后参与意向阶段的调节效应。我们的研究结果支持公关对 PAT 和 PCT 与评论意向之间关联的负中介效应,以及对购买前认可和分享的正中介效应。而公关的正向调节效应在购买后的参与意愿中得到了证实。本研究提出了一些学术和管理意义。
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来源期刊
CiteScore
5.40
自引率
16.70%
发文量
46
期刊介绍: Data has become the new ore in today’s knowledge economy. However, merely storing and reporting are not enough to thrive in today’s increasingly competitive markets. What is called for is the ability to make sense of all these oceans of data, and to apply those insights to the way companies approach their markets, adjust to changing market conditions, and respond to new competitors. Marketing analytics lies at the heart of this contemporary wave of data driven decision-making. Companies can no longer survive when they rely on gut instinct to make decisions. Strategic leverage of data is one of the few remaining sources of sustainable competitive advantage. New products can be copied faster than ever before. Staff are becoming less loyal as well as more mobile, and business centers themselves are moving across the globe in a world that is getting flatter and flatter. The Journal of Marketing Analytics brings together applied research and practice papers in this blossoming field. A unique blend of applied academic research, combined with insights from commercial best practices makes the Journal of Marketing Analytics a perfect companion for academics and practitioners alike. Academics can stay in touch with the latest developments in this field. Marketing analytics professionals can read about the latest trends, and cutting edge academic research in this discipline. The Journal of Marketing Analytics will feature applied research papers on topics like targeting, segmentation, big data, customer loyalty and lifecycle management, cross-selling, CRM, data quality management, multi-channel marketing, and marketing strategy. The Journal of Marketing Analytics aims to combine the rigor of carefully controlled scientific research methods with applicability of real world case studies. Our double blind review process ensures that papers are selected on their content and merits alone, selecting the best possible papers in this field.
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